Papers - Yoshiki YAMAGATA

Mapping urban carbon emissions in relation to local climate zones: Case of the building sector in Bangkok Metropolitan Administration, Thailand

D Khamchiangta, Y Yamagata

Energy and Built Environment (Elsevier)  5 ( 3 ) 337 - 347 2024.06

Research paper (scientific journal)

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This study focuses on carbon emissions of the building sector in relation to local climate zone (LCZ) classification, concentrating on two major parts. First, we estimated carbon emissions in the building sector, which were cal- culated for weekdays and weekends real-time daily energy consumption patterns. The estimations were divided into direct (from petroleum products consumption) and indirect emissions (from electricity consumption). Sec- ond, we examined urban carbon emissions mapping in relation to LCZ. Bangkok Metropolitan Administration (BMA) was used as the case study and 2016 as the base year for examination. The results illustrate that indirect emissions in Bangkok can be up to ten times higher than direct emissions. The analysis indicates that LCZ, such as compact high-rise, large low-rise, light industry, and warehouse zones had a relatively higher carbon emission intensity than others. Additionally, we identified that the compact high-rise zone has the highest indirect emission intensity, while the light industry and warehouse zone have the greatest direct emission intensity. These results provide insights into the dynamics of carbon emission characteristics in the building sector and the methodology purported here can be used to support low carbon city planning and policymaking in Bangkok.

Spatial exploration of rural capital contributing to quality of life and urban-to-rural migration decisions: a case study of Hokuto City, Japan

Y Takahashi, T Yoshida, S Shigeto, H Kubota, BA Johnson, Y Yamagata

Sustainability Science (Springer Japan)  19   489 - 506 2024.01

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Globally, urbanization constitutes one of the major underlying drivers of global ecological degradation. Hence, deurbanization, i.e., demographic shift from urban to distant rural areas in a way that increases quality of life (QoL), can be one of the key pathways to address this global challenge. In this study, we investigated the contribution of nature and other types of rural capital to QoL and to people’s decision to migrate from urban to rural areas by studying residents in Hokuto City, a popular urban-to-rural migration destination in Japan. An integrated analysis of the 414 responses to a questionnaire survey and open and commercial geospatial datasets representing natural, built, human, cultural, and financial capital revealed the contributions of specific elements of rural capital to people’s QoL. These included natural capital (farmland, symbolic natural sites, mountain peak view, lower temperature, and tranquility), built capital (highways, railway stations, shops, and restaurants), and financial capital (employment). Many of these are related to the reasons that migrants, including return and one-way migrants, chose their present home location in Hokuto City, indicating their intention to increase QoL by migration. Particularly, one-way migrant homes were located predominantly on higher up mountain slopes with lower temperatures, higher forest cover, near natural parks, and symbolic natural sites, and yet with easier access to railway stations and employment. These results provide a valuable evidence base for rural spatial planning for increased QoL and attracting migrants that considers ecological–social feedbacks, and hence supports deurbanization.

Assessment of unutilized woody biomass energy and the cost and greenhouse gas emissions of woody biomass power plants in Hokkaido, Japan

Ryoga Ono, Yoichiro Fukuda, Masahiko Fujii, Yoshiki Yamagata

Cleaner Energy Systems (Elsevier)  6   100084 2023.12

Digital Transformation of Logistic and Maintenance for Water/City-Gas Supply Infrastructures

Masaaki Hashimoto, Yoshiki Yamagata, Yoshiaki Ohkami

2023 International Conference on Electrical, Computer and Energy Technologies (IEEE)     1 - 6 2023.11

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This paper deals with application of cutting-edge information technology represented by Digital Transformation, DX, for maintaining critical infrastructures such as water and city-gas supply systems. Among many stakeholders related to such infrastructure, we have focused on system maintenance for the end-user by focusing on manufacturing, wholesale and retail, logistic, and on-site construction that formulate a very complex System of System. First, this paper describes a successful example of DX application to the water supply system. Second, the approach and means of this example were applied to an obsolete system of a city-gas supply system with successful results in relatively short period of time. In this DX application, there were several issues to overcome during the execution of reformation but finally the goal of this attempt has been attained by improving the process and increasing the profit. This has proven that appropriate application of the DX is useful and provides a powerful tool for improving business. Typical successful results are: 1) Service time has increased to 24 hours a day and 365 days a year. 2) Number of workforce has decreased from 37 to 27, and 3) Number of errors decreased to 1 to 4 out of 200 orders.

Mapping urban carbon emissions in relation to local climate zones: Case of the building sector in Bangkok Metropolitan Administration, Thailand

Dararat Khamchiangta, Yoshiki Yamagata

Energy and Built Environment (Elsevier)   2022.11

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This study focuses on carbon emissions of the building sector in relation to local climate zone (LCZ) classification, concentrating on two major parts. First, we estimated carbon emissions in the building sector, which were calculated for weekdays and weekends real-time daily energy consumption patterns. The estimations were divided into direct (from petroleum products consumption) and indirect emissions (from electricity consumption). Second, we examined urban carbon emissions mapping in relation to LCZ. Bangkok Metropolitan Administration (BMA) was used as the case study and 2016 as the base year for examination. The results illustrate that indirect emissions in Bangkok can be up to ten times higher than direct emissions. The analysis indicates that LCZ, such as compact high-rise, large low-rise, light industry, and warehouse zones had a relatively higher carbon emission intensity than others …

WHAT ARE THE OPPORUNITIES AND LIMITATIONS OF NEW URBAN SYSTEMS DESIGN USING DIGITAL TWIN?

Yamagata Yoshiki ,Komiya Masahito ,Chang Soowon

 2022.07

Joint Work, Lead author

COMMUNITY CARBON MANEGEMANT FRAMEWORK BY DESIGNING DIGITAL TWIN FESTIVAL USING GIS

Hideo Takahashi, Yamagata Yoshiki, Chang Soowon

 2022.07

Joint Work, Corresponding author

Spatial-Temporal CO2 Mapping for Urban Carbon Management

Yoshida Takahiro, Murayama Akito, Yamagata, Yoshiki

 2022.07

Joint Work, Last author

Smart cities and climate-resilient urban planning

Ayyoob Sharifi, Yoshiki Yamagata

Environment and Planning B: Urban Analytics and City Science (SAGE Publications)  49 ( 5 ) 1347 - 1353 2022.06

Assessment of Waterfront Office Redevelopment Plan on Optimal Building Arrangements with Rooftop Photovoltaics: A Case Study for Shinagawa, Tokyo

Younghun Choi , Takuro Kobashi , Yoshiki Yamagata and Akito Murayama

Energies (MDPI)  15 ( 3 )  2022.01

Joint Work

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Designing waterfront redevelopment generally focuses on attractiveness, leisure, and
beauty, resulting in various types of building and block shapes with limited considerations on
environmental aspects. However, increasing climate change impacts necessitate these buildings to be
sustainable, resilient, and zero CO2 emissions. By producing five scenarios (plus existing buildings)
with constant floor areas, we investigated how buildings and district forms with building integrated
photovoltaics (BIPV) affect energy consumption and production, self-sufficiency, CO2 emission, and
energy costs in the context of waterfront redevelopment in Tokyo. From estimated hourly electricity
demands of the buildings, techno-economic analyses were conducted for rooftop PV systems for 2018
and 2030 with declining costs of rooftop PV systems. We found that environmental building designs
with rooftop PV system are increasingly economical in Tokyo with CO2 emission reduction of 2–9%
that depends on rooftop sizes. Payback periods drop from 14 years in 2018 to 6 years in 2030. Toward
net-zero CO2 emissions by 2050, immediate actions are necessary to install rooftop PVs on existing
and new buildings with energy efficiency improvements by construction industry and building
owners. To facilitate such actions, national and local governments need to adopt appropriate policies.

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Rapid rise of decarbonization potentials of photovoltaics plus electric vehicles in residential houses over commercial districts

Takuro Kobashia, Younghun Choia, Yujiro Hiranob, Yoshiki Yamagataa, Kelvin Sayc

Applied Energy (Elsevier)  306 2022.01

Research paper (scientific journal), Joint Work

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Rooftop photovoltaics (PVs) integrated with electric vehicles (EVs) has the potential to deeply decarbonize urban energy systems in a cost-effective way. The SolarEV City Concept suggested that the rooftop PV plus EV systems can supply up to 95% of electricity demand within cities in Japan. However, it was not clear which district in city could consume, generate, and store the PV electricity, as each district has different load patterns, building structures, and number of parked cars. In this study, we performed techno-economic analyses on rooftop PV systems integrated with stand-alone batteries or EVs in residential and commercial districts in Japan from 2020 to 2040. We found that rooftop PV systems in 2020 are already cost competitive relative to existing energy systems. However, “PV + EV” systems in residential houses rapidly increases its economic advantage over commercial districts due to greater rooftop space and higher number of available vehicles. Moreover, energy sharing significantly improved the decarbonization potential. By 2025, energy cost savings, payback periods, and internal rate of return (IRR) of residential “PV + EV” systems respectively reached 23%, 9 years, and 11%, and continued improving in subsequent years. CO2 emissions from electricity and gasoline consumption was reduced by 88%, and the system was capable to supplying 89% of electricity demand. The results indicate that residential “PV + EV” systems are a potential source for significant renewable energy generation and storage that can also produce increasingly dispatchable electricity. Policy makers, industries, and communities should prepare to establish these systems through regulatory reform and demonstration projects to scale-up after 2025.

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Diverse values of urban-to-rural migration: A case study of Hokuto City, Japan

YasuoTakahashi, Hiroyuki Kubota, Sawako Shigeto, TakahiroYoshida, Yoshiki Yamagata

Journal of Rural Studies (Elsevier)  87   292 - 299 2021.10

Research paper (scientific journal), Joint Work, Accepted,  ISSN  0743-0167

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The global population is concentrating unprecedentedly into urban areas, raising concerns on global sustainability and human well-being. There also exists a niche trend of migration from urban to rural areas particularly in countries with post-industrial economies. This paper investigated values of migration expressed by the migrants arrived in Hokuto City, a Japanese rural municipality experiencing pervasive population decline but is also a popular destination for migrants from urban areas. Statistical analyses of 868 responses to a Hokuto City's migrant survey between April 2017 and January 2019 identified their common values of migration, i.e., nature, housing and food. In addition to these common values, households with different demographic characteristics had different priorities: employment for singles in ages between 16 and 29; favorable environment for raising children for married couples in their 30s and 40s; not specific or ‘lifestyle’ for migrants in 50s; and staying with or near family for retirees over 60 years. Knowledge of heterogeneity in migrants and of their values, as described herein, will enable targeted policies and public services concerning migration. Widespread acceptance of teleworking after experiencing the COVID-19 pandemic might offer people of working age, particularly in their 20s and younger, a wider range of options of places to work and live, and thus is likely to influence future urban-rural population flow. A more detailed analysis of the region's natural attributes which are central to the values of migration to rural areas, such as Hokuto City, will be useful to inform regional land use planning that is salient to the values of migrants.

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The Need for Urban Form Data in Spatial Modeling of Urban Carbon Emissions in China: A Critical Review

Cai, Meng, Yuan Shi, Chao Ren, Takahiro Yoshida, Yoshiki Yamagata, Chao Ding, and Nan Zhou

Journal of Cleaner Production (Elsevier)   2021.08

Joint Work

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Cities produce over 70% of global carbon emissions and are thus crucial in driving climate change. Urban carbon emissions may continue to increase especially in those less-developed countries and regions which are still under rapid urban development. Policymakers need to find ways to effectively control and reduce carbon emissions. Thus, spatial modeling methods to map and predict urban carbon emissions have been developed to meet these needs. This paper examines the progress of the spatial modeling of carbon emissions and the relationship between urban form and carbon emissions in China by reviewing more than 100 peer-reviewed journal articles in the Scopus database. The latest prediction methods and techniques are described in the paper. Their advantages and limitations are then discussed. Urban forms have a significant influence on carbon emissions and have been applied in spatial modeling studies in other countries. However, this review has identified the lack of urban form data and high-resolution inventories from existing studies in China. Future developments in the spatial modeling in China should therefore have a fine spatial resolution and incorporate open and high-quality urban form data, including urban morphology and land use/land cover.

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Machine learning model for predicting out-of-hospitalcardiac arrests using meteorological and chronological data

Takahiro Nakashima , Soshiro Ogata , Teruo Noguchi , Yoshio Tahara , Daisuke Onozuka , Satoshi Kato , Yoshiki Yamagata , Sunao Kojima , Taku Iwami , Tetsuya Sakamoto , Ken Nagao , Hiroshi Nonogi , Satoshi Yasuda , Koji Iihara , Robert Neumar , Kunihiro Nishimura

 2021.05

Joint Work

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Objectives: To evaluate a predictive model for robust estimation of daily out-of-hospital cardiac arrest (OHCA) incidence using a suite of machine learning (ML) approaches and high-resolution meteorological and chronological data.

Methods: In this population-based study, we combined an OHCA nationwide registry and high-resolution meteorological and chronological datasets from Japan. We developed a model to predict daily OHCA incidence with a training dataset for 2005-2013 using the eXtreme Gradient Boosting algorithm. A dataset for 2014-2015 was used to test the predictive model. The main outcome was the accuracy of the predictive model for the number of daily OHCA events, based on mean absolute error (MAE) and mean absolute percentage error (MAPE). In general, a model with MAPE less than 10% is considered highly accurate.

Results: Among the 1 299 784 OHCA cases, 661 052 OHCA cases of cardiac origin (525 374 cases in the training dataset on which fourfold cross-validation was performed and 135 678 cases in the testing dataset) were included in the analysis. Compared with the ML models using meteorological or chronological variables alone, the ML model with combined meteorological and chronological variables had the highest predictive accuracy in the training (MAE 1.314 and MAPE 7.007%) and testing datasets (MAE 1.547 and MAPE 7.788%). Sunday, Monday, holiday, winter, low ambient temperature and large interday or intraday temperature difference were more strongly associated with OHCA incidence than other the meteorological and chronological variables.

Conclusions: A ML predictive model using comprehensive daily meteorological and chronological data allows for highly precise estimates of OHCA incidence.

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Carbon analytics for net-zero emissions sustainable cities

Anu Ramaswami, Kangkang Tong, Josep G. Canadell, Robert B. Jackson, Eleanor (Kellie) Stokes, Shobhakar Dhakal, Mario Finch, Peraphan Jittrapirom, Neelam Singh, Yoshiki Yamagata, Eli Yewdall, Leehi Yona & Karen C. Seto

Nature sustainability (Springer)  4 ( 6 ) 460 - 463 2021.05

Joint Work

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Consensus on carbon accounting approaches at city-level is lacking and analytic frameworks to systematically link carbon mitigation with the Sustainable Development Goals are limited. A new accounting approach anchored upon key physical provisioning systems can help to address these knowledge gaps and facilitate urban transitions.

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Estimating Building Electricity Performance Gaps with Internet of Things Data Using Bayesian Multilevel Additive Modeling

Chang S, Castro-Lacouture D, Yamagata Y

Journal of Construction Engineering and Management (Journal of Construction Engineering and Management)  146 ( 12 )  2020.12

Joint Work,  ISSN  07339364

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Energy models should be simplified to handle data limitations and should predict reliable energy use. Currently, it remains challenging to ensure an appropriate level of detail for simplifying building energy models and to avoid performance gaps when predicting electricity consumption. In this respect, this research proposes to identify an appropriate level of simplifying a building energy model, predict electricity demands and performance gaps using the simplified energy model, and expand the model usability through the operational stage. Building electricity demands predicted through EnergyPlus (version 8.7.0) simulation are compared with actual electricity data collected through Internet of Things (IoT) sensors. Consideration of performance gaps increases the predictability of electricity consumption of a simplified energy model. Also, the Bayesian multilevel additive model updates the performance gaps along with the collection of new IoT data. The findings of this study contribute to forecasting electricity demands with a simplified energy model by predicting performance gaps that can be applied to predicting the electricity needs of similar buildings in the design stage and controlling operational electricity use in the operational stage by comparing sensor measurement with reference data provided by the energy model.

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Spatiotemporal analysis of deforestation in the Chapare region of Bolivia using LANDSAT images

Bagan H, Millington A, Takeuchi W, Yamagata Y

Land Degradation and Development (Land Degradation and Development)  31 ( 18 ) 3024 - 3039 2020.12

Research paper (scientific journal), Joint Work,  ISSN  10853278

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The purpose of this study is to quantify (a) spatiotemporal deforestation patterns, and (b) the relationships between changes in the main land-cover types in the Chapare region of Bolivia. We applied subspace classification methods to LANDSAT data from 1986, 1999, and 2018 and used grid cells at scales of 150, 300, 600, and 900 m to measure deforestation trajectories. The 150 m grids provided better detail to determine deforestation trajectories than coarser-scale grid cells. Differences in grid-cell scale did not influence the statistical trends in land-cover changes significantly. Changes in forest area were negatively correlated with changes in cropland (r = −.44), grassland (r = −.34), swamp grassland (r = −.38), and regrowth (r = −.32) areas. Correlations between forest losses in cropland, grassland, and regrowth change analyses were weaker between 1999 and 2018 compared to 1986 to 1999. Forest cover declined from 6,635 km (1986) to 3,800 km (2018), and the deforestation rate increased from an annual average of 1.36% between 1986 and 1999 to 2.0% between 1999 and 2018. The key proximate drivers of forest clearance rates and patterns were increasing population, agricultural expansion, and road building. While coca is an economically important crop in Chapare, its direct and indirect effects on deforestation could not be determined unambiguously. It is probable that the expansion of agriculture will lead to further deforestation and forest fragmentation and, along with decreases in forest cover, further changes will take place between non-forest categories. 2 2

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Decision support for retrofitting building envelopes using multi-objective optimization under uncertainties

Chang S., Castro-Lacouture D., Yamagata Y.

Journal of Building Engineering (Journal of Building Engineering)  32 2020.11

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In the last decade, retrofitting strategies have been reviewed to improve energy efficiency and reduce the environmental impact of existing buildings. One retrofitting strategy consists of innovating building envelopes with the adoption of high-performance materials or systems. Despite the potential performance enhancement, opportunities for new envelopes have been constrained because various envelope options are difficult to be evaluated synthetically. Also, the decisions should consider the optimization of multiple objectives as well as uncertainties. In this respect, this paper aims to support the decision of selecting building envelopes to meet multiple objectives under uncertainties while considering possible envelope options. A multi-objective optimization model is developed considering the existing built form, uncertainties in performance predictions, and incorporating newly developed façade systems. The optimal selection includes emerging materials and technologies that are provided with building envelope renovation options to satisfy indoor thermal comfort, energy balance, environmental emissions, and economic aspects. The decision-support framework is also devised to add any envelope options. This adaptable framework enables decision makers to accommodate new system materials and proactively evaluate their feasibility. The optimization model and framework proposed in this research will contribute to providing a roadmap for transforming existing buildings into smart and sustainable built systems.

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MIROC-INTEG-LAND version 1: A global biogeochemical land surface model with human water management, crop growth, and land-use change

Yokohata T, Kinoshita T, Sakurai G, Pokhrel Y, Ito A, Okada M, Satoh Y, Kato E, Nitta T, Fujimori S, Felfelani F, Masaki Y, Iizumi T, Nishimori M, Hanasaki N, Takahashi K, Yamagata Y, Emori S

Geoscientific Model Development (Geoscientific Model Development)  13 ( 10 ) 4713 - 4747 2020.10

Research paper (scientific journal), Joint Work,  ISSN  1991959X

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Future changes in the climate system could have significant impacts on the natural environment and human activities, which in turn affect changes in the climate system. In the interaction between natural and human systems under climate change conditions, land use is one of the elements that play an essential role. On the one hand, future climate change will affect the availability of water and food, which may impact land-use change. On the other hand, human-induced land-use change can affect the climate system through biogeophysical and biogeochemical effects. To investigate these interrelationships, we developed MIROC-INTEG-LAND (MIROC INTEGrated LAND surface model version 1), an integrated model that combines the land surface component of global climate model MIROC (Model for Interdisciplinary Research on Climate) with water resources, crop production, land ecosystem, and land-use models. The most significant feature of MIROC-INTEG-LAND is that the land surface model that describes the processes of the energy and water balance, human water management, and crop growth incorporates a land use decision-making model based on economic activities. In MIROC-INTEG-LAND, spatially detailed information regarding water resources and crop yields is reflected in the prediction of future land-use change, which cannot be considered in the conventional integrated assessment models. In this paper, we introduce the details and interconnections of the submodels of MIROC-INTEG-LAND, compare historical simulations with observations, and identify various interactions between the submodels. By evaluating the historical simulation, we have confirmed that the model reproduces the observed states well. The future simulations indicate that changes in climate have significant impacts on crop yields, land use, and irrigation water demand. The newly developed MIROC-INTEG-LAND could be combined with atmospheric and ocean models to develop an integrated earth system model to simulate the interactions among coupled natural-human earth system components.

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On the potential of “Photovoltaics + Electric vehicles” for deep decarbonization of Kyoto's power systems: Techno-economic-social considerations

Kobashi T., Yoshida T., Yamagata Y., Naito K., Pfenninger S., Say K., Takeda Y., Ahl A., Yarime M., Hara K.

Applied Energy (Applied Energy)  275 2020.10

ISSN  03062619

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To minimize the impacts of climate change, it is increasingly clear that global CO emissions should be eliminated by 2050 and that leading low-carbon cities should reach net zero emissions by 2040. However, the precise pathways by which they can reach such ambitious goals have yet to be identified. As costs of photovoltaics (PV), batteries, and electric vehicles (EVs) are likely to keep falling, they can jointly play a key role for deep decarbonization. Here, we conduct a techno-economic analysis of a city-scale energy system with roof-top PV, batteries, and EVs for Kyoto City, Japan. We find that aggressive EV adoption and the use of EVs for electricity storage could help roof-top PV penetration in the city with substantially lower costs than just deploying PV and batteries alone or allowing EV to charge only. CO emissions from vehicle and electricity usage in the city could be reduced by 60–74% if the entire current car fleet is replaced by EVs while also reducing energy costs by 22–37% by 2030. The largest challenge of a city-wide “PV + EV” system (named as “Solar-EV city”) is its implementation. We explore how it could be realized in Kyoto through peer-to-peer (P2P) power trading/blockchain technology initially on a community scale as smart microgrids, then gradually expanding/converging into a city-wide. For the transition to decentralized power systems, citizen's decision-making process is one of the keys to overcome social, institutional, and regulatory barriers. 2 2

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Systematizing and upscaling urban climate change mitigation

Creutzig F, Bai X, Khosla R, Viguie V, Yamagata Y

Environmental Research Letters (Environmental Research Letters)  15 ( 10 )  2020.10

Joint Work,  ISSN  17489318

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The question of what cities can contribute to mitigation and adapting to climate change is gaining traction among researchers and policy makers alike. However, while the field is rich with case studies, methods that provide rich data across municipalities and potentially at global scale remain underdeveloped, and comparative insights remain scarce. Here we summarize contributions to the focus issue on 'Systematizing and Upscaling Urban Climate Solutions', also drawing from presentations given at an accompanying conference in 2018. We highlight four core areas for systematizing and upscaling urban climate mitigation solutions. First, with more and better (big) data and associated machine learning methods, there is increasing potential to compare types of cities and leverage collective understanding. Second, while urban climate assessments have mostly emphasized urban planning, demand-side action as related to both behavioral change and modified social practices relevant to urban space deserve more academic attention and integration across a diverse set of social sciences. Third, climate mitigation would be intangible as a single objective at the urban scale, and measures and solutions that coordinate mitigation coherently with adaptation and broader sustainable development goals require explicit conceptualization and systematization. Forth, all insights should come together to develop governance frameworks that translate scientific exercises into concrete, realistic and organized action plans on the ground, for all cities.

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Rethinking sustainable bioenergy development in Japan: decentralised system supported by local forestry biomass

Goh C.S, Aikawa T, Ahl A, Ito K, Kayo C, Kikuchi Y, Takahashi Y, Furubayashi T, Nakata T, Kanematsu Y, Saito O, Yamagata Y

Sustainability Science (Sustainability Science)  15 ( 5 ) 1461 - 1471 2020.09

Research paper (scientific journal), Joint Work,  ISSN  18624065

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Bioenergy has been promoted in Japan with ambitious targets. However, the incentive schemes excluded renewable heat and overlooked synergies with local forest management, leading to the development of large-scale biomass plants that heavily rely on overseas biomass supplies. This case report discussed an alternative scenario of decentralised bioenergy systems supported with local biomass through five important questions. The currently available knowledge indicates that such a scenario is feasible with integrative forest management that considers both ecosystem services and multiple uses of wood. In addition to various environmental benefits, replacing imported fossil fuels with local biomass can also enhance energy security. Realising this scenario requires careful consideration of local context, empowerment of local governments and encouragement of both public and private initiatives.

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Urban land cover mapping under the Local Climate Zone scheme using Sentinel-2 and PALSAR-2 data

La Y., Bagan H., Yamagata Y.

Urban Climate (Urban Climate)  33 2020.09

ISSN  22120955

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The spatial and spectral heterogeneity of urban areas makes land cover classification a challenging process. In this study, we highlight the potential of combined multi-spectral Sentinel-2 and fully polarimetric PALSAR-2 data for land cover classification in dense urban areas, based on the Local Climate Zone (LCZ) scheme. We classified differently combined spectral and back-scattering characteristics using the subspace method in comparison with the Support Vector Machine (SVM) and Maximum Likelihood Classifier (MLC) methods. Results show that, (i) the overall accuracy (OA) was 65.9% for the Sentinel-2 data, (ii) higher OA (71.9%) was achieved by adding four intensity images of PALSAR-2 to Sentinel-2, (iii) the inclusion of decomposed components increased OA to 72.8%, and (iv) the highest OA (73.3%) was achieved using all features. These results suggest that the inclusion of different backscattering characteristics disproportionately improved classification accuracy from using multi-spectral data alone. The results of comparison between different methods show that the subspace method performed better than SVM and MLC, particularly when high-dimensional data were used. The subspace method classified particularly well for some specific LCZ classes which are easily mixed between each other. It provides a promising option for LCZ mapping.

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On the Potential of 'PV + EV' for Deep Decarbonization of Kyoto’s Power Systems: Techno-Economic-Social Considerations

Kobashi, Takuro, Takahiro Yoshida, Yoshiki Yamagata, Katsuhiko Naito, Stefan Pfenninger, Kelvin Say, Yasuhiro Takeda, Amanda Ahl, Masaru Yarime, Keishiro Hara

Applied Energy Forthcoming 2020.06

Research paper (scientific journal), Joint Work, Accepted

Techno-economic assessment of photovoltaics plus electric vehicles towards household-sector decarbonization in Kyoto and Shenzhen by the year 2030

Kobashi T., Say K., Wang J., Yarime M., Wang D., Yoshida T., Yamagata Y.

Journal of Cleaner Production (Journal of Cleaner Production)  253 2020.04

ISSN  09596526

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Finding economical and sustainable pathways for the deployment of renewables is critical for the success of decarbonizing energy systems. Because of the variable nature of renewable energy, however, the integration of renewables becomes increasingly costly and difficult as the renewable penetration becomes higher. The recent rise of electric vehicles (EVs) provides us with an opportunity to increase self-consumption of solar photovoltaic (PV) at households with substantially lower additional costs. In this paper, an environmental techno-economic assessment of residential PV systems is conducted with battery or EVs allowing charging and discharging (Vehicle to Home: V2H) in Kyoto, Japan, and Shenzhen, China, incorporating the cost projections of these technologies towards 2030. It is found that “PV + EV” (V2H) becomes highly cost-effective towards 2030 in Kyoto in comparison with “PV only”, “PV + battery”, and “EV charge”. In the region of lower electricity costs such as Shenzhen, switching to EVs from gasoline vehicles is the most cost-effective option during 2020s. Finally, it is found that “PV + EV” has the highest CO emission reduction potential across all the technology combinations considered, owing to EV charging of carbon-free electricity from PV. To facilitate a rapid household decarbonization, policy makers should reinforce policies to enhance the penetration of combined technologies of “PV + EV” (V2H) towards 2030. 2

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Energy sharing boundaries integrating buildings and vehicles tangled in spatial and temporal changes

Chang S, Yoshida T, Binder R.B, Yamagata Y, Castro-Lacouture D

Construction Research Congress 2020: Infrastructure Systems and Sustainability - Selected Papers from the Construction Research Congress 2020 (Construction Research Congress 2020: Infrastructure Systems and Sustainability - Selected Papers from the Construction Research Congress 2020)     434 - 443 2020

Research paper (international conference proceedings), Joint Work,  ISSN  9780784482858

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Technical advancements such as building-integrated renewable systems and autonomous vehicles (AVs) require existing electricity grids to be transformed into adaptable microgrids considering future energy supply and demand. Interactions between energy demanders and suppliers should be predicted to quickly respond and adapt to future demands or uncertain events. However, communities consisting of buildings, transports, and people are complex and their interactions are difficult to be recognized. This research investigates the interactions among elements in communities featuring AVs and solar photovoltaics (PV)-integrated buildings. A framework for establishing smart energy networks that can be adjustable spatially and temporally is developed by communicating buildings and vehicles. The methodology is tested in buildings and road networks in Kyojima 1, North Sumida, Tokyo, Japan. Existing energy demands and transportation systems are reviewed to establish future scenarios for applying AVs and solar PV buildings. The scenarios are analyzed using community clustering and Voronoi diagram algorithms, in which sustainable community boundaries are examined using prediction data from parametric energy modeling and spatial network analysis. The framework can support decision-making for future community boundaries, thereby distributing energy securely and efficiently. This research will also contribute to preparing communities to share energy information and to achieve resilient and sustainable infrastructure systems.

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Modeling and design of smart buildings

Soowon Chang, Perry P.J. Yang, Yoshiki Yamagata, Michael B. Tobey

Urban Systems Design (Elsevier)     59 - 86 2020

Joint Work, Accepted

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Spatial modeling and design of smart communities

Takahiro Yoshida, Yoshiki Yamagata, Soowon Chang, Vincent de Gooyert, Hajime Seya, Daisuke Murakami, Peraphan Jittrapirom, Gerasimos Voulgaris

Urban Systems Design (Elsevier)     199 - 255 2020

Joint Work, Accepted

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Spatial scenario creation based on downscale methods

Murakami D., Yamagata Y.

Spatial Analysis Using Big Data: Methods and Urban Applications (Spatial Analysis Using Big Data: Methods and Urban Applications)     259 - 270 2019.11

ISSN  9780128131275

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This chapter introduces a spatial econometric model application to a downscaling of global socioeconometric scenarios. Section 10.1 provides a brief review of relevant literature. Section 10.2 describes our downscale approach and Section 10.3 employs it to estimate populations and GDPs by 0.5-degree grids. Finally, Section 10.4 concludes our discussion.

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Models in quantitative geography

Murakami D., Yamagata Y.

Spatial Analysis Using Big Data: Methods and Urban Applications (Spatial Analysis Using Big Data: Methods and Urban Applications)     159 - 178 2019.11

ISSN  9780128131275

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This chapter introduces approaches in quantitative geography. After the introduction in Section 6.1, Sections 6.2 and 6.3 explain the geographically weighted regression and the spatial filtering approaches, respectively. Section 6.4 describes extensions of these approaches for large spatial dataset.

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Mathematical preparation

Seya H., Yamagata Y.

Spatial Analysis Using Big Data: Methods and Urban Applications (Spatial Analysis Using Big Data: Methods and Urban Applications)     9 - 31 2019.11

ISSN  9780128131275

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Section 2.1 of this chapter defines the typical notations. Section 2.2 explains the classical linear regression model with typical assumptions and discusses what may happen when these assumptions are violated. Estimation techniques such as ordinary least squares, two-stage least squares, and generalized method of moments are briefly explained. Sections 2.3 and 2.4 introduce two advanced regression models, the generalized linear model and the additive model. Section 2.5 explains the basics of Bayesian statistics and the Markov chain Monte Carlo in terms of a regression model.

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Geostatistics and Gaussian process models

Murakami D., Yamagata Y., Hirano T.

Spatial Analysis Using Big Data: Methods and Urban Applications (Spatial Analysis Using Big Data: Methods and Urban Applications)     57 - 112 2019.11

ISSN  9780128131275

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In this chapter, Section 4.1 briefly introduces the history of geostatistics. Section 4.2 explains stationary spatial processes and the basic geostatistical model to describe the process; Section 4.3 explains how to estimate the model parameters. After introducing Kriging, which is the spatial interpolation approach, in Section 4.4, Section 4.5 introduces its extensions including linear and non-linear kriging approaches. Then, Sections 4.6, 4.7, and 4.8, respectively, explain semiparametric, Bayesian, and spatiotemporal extensions of the geostatistical approach. Finally, Section 4.9 explains geostatistical approaches for large samples.

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Evaluating walkability using mobile GPS data

Yamagata Y., Murakami D., Yoshida T.

Spatial Analysis Using Big Data: Methods and Urban Applications (Spatial Analysis Using Big Data: Methods and Urban Applications)     239 - 257 2019.11

ISSN  9780128131275

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This chapter illustrates the results of applications of geographically weighted regression modeling (Chapter 6) for assessing goodness of walking environment, that is, walkability. Section 9.1 briefly introduces some representative measures of walkability. Section 9.2 explains about using data and walkability measures. The settings for geographically weighted regression modeling are also explained here. Sections 9.3 and 9.4 show the estimation results. The former focuses on the impact of pedestrian network structure on the number of pedestrians, whereas the latter focuses on heatwave risk for pedestrians at an intra-urban scale. Finally, Section 9.5 concludes this chapter with a discussion.

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Quasi real-time energy use estimation using Google's Popular Times data

Yoshida T., Yamagata Y.

Spatial Analysis Using Big Data: Methods and Urban Applications (Spatial Analysis Using Big Data: Methods and Urban Applications)     271 - 280 2019.11

ISSN  9780128131275

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This chapter illustrates a geostatistic model (Chapter 4) application to estimate quasi real-time energy consumption in each building using Google's Popular Times data. After the introduction in Section 11.1 where our research motivations are explained, Section 11.2 describes the empirical methods, and we adopt compositional kriging approach for this analysis. Section 11.3 shows the estimation results of estimating building-level energy consumption. Effective visualization is attempted with the results. Section 11.4 concludes this chapter with a discussion.

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Spatial econometric models

Seya H., Yoshida T., Yamagata Y.

Spatial Analysis Using Big Data: Methods and Urban Applications (Spatial Analysis Using Big Data: Methods and Urban Applications)     113 - 158 2019.11

ISSN  9780128131275

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Section 5.1 of this chapter provides a brief review of spatial econometrics. Section 5.2 describes various types of spatial econometric models. Impact measures are also explained here. Section 5.3 explains representative parameter estimation methods for spatial econometric models. Sections 5.4 and 5.5 introduce likelihood-based tests for spatial autocorrelation and spatial heterogeneity, respectively. Section 5.6 explains the remaining important models that were not explained in Section 5.2. Finally, Section 5.7 explores the methods that seem useful when we apply spatial econometric models to a large dataset.

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Spatial heat-wave assessments using geotagged Twitter data

Murakami D., Yamagata Y.

Spatial Analysis Using Big Data: Methods and Urban Applications (Spatial Analysis Using Big Data: Methods and Urban Applications)     227 - 238 2019.11

ISSN  9780128131275

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This chapter introduces a twitter data application to a heatwave analysis. Section 8.1 introduces our discussion emphasizing on statistical modeling combining different types of spatial data. Section 8.2 introduces the twitter data and their processing. Section 8.3 explains our analysis method, and Section 8.4 applies this method to a heatwave analysis. Section 8.5 concludes our discussion.

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Typologies of Rapid Urbanization in Developing Asian Countries: A Study of Shanghai's Rapid Urbanization and Subsequent Strategies

Boynton Tobey M, Chang S, Brent Binder R, Yamagata Y

IOP Conference Series: Earth and Environmental Science (IOP Conference Series: Earth and Environmental Science)  294 ( 1 )  2019.08

Joint Work,  ISSN  17551307

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Over the last several decades developing countries, especially in Asia, have undergone large scale rapid urbanization, impacting their developmental patterns. Compounded with increased economic prosperity and social mobility attracting individuals and companies, to urban centres, has led to severe administrative challenges that can negatively affect the citizens, nation, and environment. In efforts to mitigate those adverse side effects cities have instituted, or citizens naturally adopted, a variety of strategies to address those issues. These strategies result in the typologies of rapid urbanization that are most prevalent in developing Asian cities. By focusing on Asian and Chinese cities, using shanghai as a test case, this research proposes several major typological categories associated with rapidly urbanizing areas. Shanghai's rapid urbanization has been shaped by seven main typologies of urban growth and expansion, since the implementation of China's economic growth policies and its resurgence as an influential global city. Spatial typological patterns of urban growth in Shanghai are analyzed to explain how the economic prosperity and social mobility have been managed. Typological adaptations learned from the historical urban expansion provide the subsequent strategies for future sustainable development in a rapidly urbanizing area.

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Assessing nighttime lights for mapping the urban areas of 50 cities across the globe

Bagan H., Borjigin H., Yamagata Y.

Environment and Planning B: Urban Analytics and City Science (Environment and Planning B: Urban Analytics and City Science)  46 ( 6 ) 1097 - 1114 2019.07

ISSN  23998083

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Nighttime data from the Defense Meteorological Satellite Program Operational Linescan System have been widely used to map urban/built-up areas (hereafter referred to as “built-up area”), but to date there has not been a geographically comprehensive evaluation of the effectiveness of using nighttime lights data to map urban areas. We created accurate, convenient, and scalable grid cells based on Defense Meteorological Satellite Program/Operational Linescan System nighttime light pixels. We then calculated the density of Landsat-derived built-up areas within each grid cell. We explored the relationship between Defense Meteorological Satellite Program/Operational Linescan System nighttime lights data and the density of built-up areas to assess the utility of nighttime lights for mapping urban areas in 50 cities across the globe. We found that the brightness of nighttime lights was only in moderate agreement with the density of built-up areas; moreover, correlations between nighttime lights and Landsat-derived built-up areas were weak. Even in relatively sparsely populated urban regions (where the density of the built-up area is less than 20%), the highest correlation coefficient (R ) was only 0.4. Furthermore, nighttime lights showed lighted areas that extended beyond the area of large cities, and nighttime lights reduced the area of small cities. The results suggest that it is difficult to use the regression model to calibrate the Defense Meteorological Satellite Program/Operational Linescan System nighttime lights to fit urban built up areas. 2

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Verification on Evacuation of Flood Disaster by Using GPS: Case Study in Mabi, Japan 2018

Yoshida T., Hiroi K., Yamagata Y., Murakami D.

International Geoscience and Remote Sensing Symposium (IGARSS) (International Geoscience and Remote Sensing Symposium (IGARSS))     5633 - 5635 2019.07

ISSN  9781538691540

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This study attempts to simulate people flow before and after the flooding in the West Japan heavy rain on July 2018, using a mobile GPS (global positioning system) data. We focus on Mabi-Cho, Kurashiki-City, which is one of the most damaged area on the flood disaster. A Monte Carlo simulation approach is introduced to generate micro-scale people's evacuation flows from spatially sparse GPS information. The result shows that GPS data effectively simulate people flow after flooding even if the simulation approach is very simple, and how people flow changed before and after the disaster.

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Spatiotemporal Heatwave Risk Evaluation: Considering Hazard, Exposure, and Vulnerability

Yamagata Y., Murakami D., Yoshida T.

International Geoscience and Remote Sensing Symposium (IGARSS) (International Geoscience and Remote Sensing Symposium (IGARSS))     5524 - 5527 2019.07

ISSN  9781538691540

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Urban heatwave is increasingly severe as the global warming advances. Even worse, especially in Japan, an increasing proportion of residences are vulnerable against heats under the aging society. Today, heatwave monitoring is an emergent task toward climate adaptive urban development. Our final goal is developing a smart navigation system to monitor real-time and micro-scale heatwave risk in Tokyo. To achieve it, we performed the following observation experiments: collection people location data with age information and people sentiment data by twitter, ground surface temperature monitoring by airborne and from the Tokyo Sky Tree. A method to combine these multi-scale information is developed to estimate micro-scale spatiotemporal behavior on heatwave risks. Based on the result, it is discussed how we can achieve the real-time and micro-scale heatwave monitoring, and make Tokyo more heat risk mitigative.

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Spatiotemporal Heatwave Risk Modeling Combining Multiple Observations

Murakami D., Yamagata Y., Yoshida T., Matsui T.

International Geoscience and Remote Sensing Symposium (IGARSS) (International Geoscience and Remote Sensing Symposium (IGARSS))     5516 - 5519 2019.07

ISSN  9781538691540

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Urban heatwave is increasingly severe as the global warming advances. Even worse, in Tokyo, an increasing proportion of residences are vulnerable against heats under the aging society. Today, heatwave monitoring is an emergent task toward climate adaptive urban development. Our final goal is developing a system to monitor real-time and micro-scale heatwave risk in Tokyo. To achieve it, we performed the following observation experiments: airborne monitoring, monitoring from the Tokyo Sky Tree, and micro-scale monitoring censoring inside and outside comforts. A method to combine these multi-scale information is developed to estimate micro-scale spatiotemporal behavior on heatwave risks. Based on the result, it is discussed how we can achieve the real-time and micro-scale heatwave monitoring, and make Tokyo more risk adaptive.

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A GPS-Based Simple Evaluation Simulation Approach: Case Study in Joso, Japan

Murakami D., Matsui T., Yoshida T., Yamagata Y.

International Geoscience and Remote Sensing Symposium (IGARSS) (International Geoscience and Remote Sensing Symposium (IGARSS))     5636 - 5637 2019.07

ISSN  9781538691540

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This study attempts to simulate evaluation flow after the flooding in the Kanto-Tohoku heavy rain in September 2015, using a mobile GPS data. A simple Monte Carlo approach is introduced to simulate micro-scale people flow from spatially sparse GPS information. The simulation result shows that GPS data effectively recovers people flow after flooding even if the simulation approach is very simple.

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Pathway using WUDAPT's Digital Synthetic City tool towards generating urban canopy parameters for multi-scale urban atmospheric modeling

Ching J., Aliaga D., Mills G., Masson V., See L., Neophytou M., Middel A., Baklanov A., Ren C., Ng E., Fung J., Wong M., Huang Y., Martilli A., Brousse O., Stewart I., Zhang X., Shehata A., Miao S., Wang X., Wang W., Yamagata Y., Duarte D., Li Y., Feddema J., Bechtel B., Hidalgo J., Roustan Y., Kim Y.S., Simon H., Kropp T., Bruse M., Lindberg F., Grimmond S., Demuzure M., Chen F., Li C., Gonzales-Cruz J., Bornstein B., He Q., Tzu-Ping , Hanna A., Erell E., Tapper N., Mall R.K., Niyogi D.

Urban Climate (Urban Climate)  28 2019.06

ISSN  22120955

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The WUDAPT (World Urban Database and Access Portal Tools project goal is to capture consistent information on urban form and function for cities worldwide that can support urban weather, climate, hydrology and air quality modeling. These data are provided as urban canopy parameters (UCPs)as used by weather, climate and air quality models to simulate the effects of urban surfaces on the overlying atmosphere. Information is stored with different levels of detail (LOD). With higher LOD greater spatial precision is provided. At the lowest LOD, Local Climate Zones (LCZ)with nominal UCP ranges is provided (order 100 m or more). To describe the spatial heterogeneity present in cities with great specificity at different urban scales we introduce the Digital Synthetic City (DSC)tool to generate UCPs at any desired scale meeting the fit-for-purpose goal of WUDAPT. 3D building and road elements of entire city landscapes are simulated based on readily available data. Comparisons with real-world urban data are very encouraging. It is customized (C-DSC)to incorporate each city's unique building morphologies based on unique types, variations and spatial distribution of building typologies, architecture features, construction materials and distribution of green and pervious surfaces. The C-DSC uses crowdsourcing methods and sampling within city Testbeds from around the world. UCP data can be computed from synthetic images at selected grid sizes and stored such that the coded string provides UCP values for individual grid cells.

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Flood Area Estimation Using Personal Location Data - Case Study of Japan Floods in 2018

Hiroi K., Yoshida T., Yamagata Y., Kawaguchi N.

2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019 (2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019)     285 - 291 2019.03

ISSN  9781538691519

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This research proposes a flood area estimation method in urban areas using personal location data. Many studies have investigated the estimation of flood levels; however, the majority of these previous works are based on the flood monitoring data. The main cause of flood disaster death is drowning due to evacuation delay in the area where observation equipment is not installed, so it is difficult to estimate flood occurrence by the previous method based only on monitoring data. In this research, we propose an estimation method that does not rely on monitoring data and instead estimates flood areas using GPS data collected from smartphones owned by the affected people. This method detects anomaly areas to analyze temporal and spatial changes of an area where a personal movement during a flooding event differs from that during regular times from personal location data. For anomaly detection, we use a dynamic time warping method with fixed window size and inequality metrics to estimate the area where an anomaly event occurred in 2 km grids. We applied this method to Kurashiki city, Okayama Prefecture, where there 52 people died during a flood that occurred in Japan in 2018. Our method found that, at the flooding time, the anomaly occurrence was estimated correctly in the area where inundation actually occurred.

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Optimization of local microgrid model for energy sharing considering daily variations in supply and demand

Murakami D., Yamagata Y., Yoshida T., Matsui T.

Energy Procedia (Energy Procedia)  158   4109 - 4114 2019

ISSN  18766102

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This study develops an approach for optimizing the size/scale of microgrids used in electricity sharing around each residence by considering the uncertainty between the electricity supply from photovoltaics and electricity demand. Uncertainties are quantified using simulations that consider actual daily variations in supply and demand. The developed approach is applied to microgrid optimization in Sumida-ku, Tokyo, Japan, and results suggests that large-scale microgrids are required in central districts but small microgrids are sufficient in old residential areas. Results also show the statistically significant effect of optimizing microgrids to enhance energy self-sufficiency.

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Estimation of gridded population and GDP scenarios with spatially explicit statistical downscaling

Murakami D., Yamagata Y.

Sustainability (Switzerland) (Sustainability (Switzerland))  11 ( 7 )  2019

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This study downscales the population and gross domestic product (GDP) scenarios given under Shared Socioeconomic Pathways (SSPs) into 0.5-degree grids. Our downscale approach has the following features. (i) It explicitly considers spatial and socioeconomic interactions among cities, (ii) it utilizes auxiliary variables, including road network and land cover, (iii) it endogenously estimates the influence from each factor by a model ensemble approach, and (iv) it allows us to control urban shrinkage/dispersion depending on SSPs. It is confirmed that our downscaling results are consistent with scenario assumptions (e.g., concentration in SSP1 and dispersion in SSP3). Besides, while existing grid-level scenarios tend to have overly-smoothed population distributions in nonurban areas, ours does not suffer from the problem, and captures the difference in urban and nonurban areas in a more reasonable manner. Our gridded dataset, including population counts and gross productivities by 0.5 degree grids by 10 years, are available from http://www.cger.nies.go.jp/gcp/population-and-gdp.html.

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Energy demand estimation using quasi-real-time people activity data

Yoshida T., Yamagata Y., Murakami D.

Energy Procedia (Energy Procedia)  158   4172 - 4177 2019

ISSN  18766102

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This study proposes an approach to estimate quasi-real-time electricity/energy demand in each commercial building using Google's Populartime data. The Populartime data records real-time human locations/activities that are collected from users of Google's maps on smartphones. The proposed approach considering changes by hour and by day of the week is applied to Sumida-ward, Tokyo, Japan. The result suggests the usefulness of our approach for energy demand monitoring considering quasi-real-time human activities.

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Big-data analysis for carbon emission reduction from cars: Towards walkable green smart community

Yamagata Y., Murakami D., Wu Y., Yang P.P.J., Yoshida T., Binder R.

Energy Procedia (Energy Procedia)  158   4292 - 4297 2019

ISSN  18766102

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To achieve low carbon cities or green smart city, it is very important to foresee how we can reduce the number of cars in the residential communities without losing convenience and comfort of people. For that purpose, walkability is one of the key performance indicators expressing the environmental quality of a district. As the first step for creating a low-carbon smart community, this study attempts to evaluate the influence of walkability on traffic behavior of people by using mobile GPS data. Specifically, we statistically analyze the relationship between various walkability indices (centrality, betweenness, angularity, etc.) evaluated by road network data, and pedestrian movement estimated by mobile GPS data in the six main wards in Tokyo, Japan. The result suggests the usefulness of our approach for low-carbon smart community design rousing people's walking activity. The walkability results and data are then compared to the results of a macrosimulation traffic model for the Sumida Ward of Tokyo to understand the impact that walkability may have on emissions if built environment conditions are improved in favor of a lesser automobile mode share.

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A global dataset of co<inf>2</inf> emissions and ancillary data related to emissions for 343 cities

Nangini C., Peregon A., Ciais P., Weddige U., Vogel F., Wang J., Bréon F.M., Bachra S., Wang Y., Gurney K., Yamagata Y., Appleby K., Telahoun S., Canadell J.G., Grübler A., Dhakal S., Creutzig F.

Scientific Data (Scientific Data)  6 2019

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We present a global dataset of anthropogenic carbon dioxide (CO ) emissions for 343 cities. The dataset builds upon data from CDP (187 cities, few in developing countries), the Bonn Center for Local Climate Action and Reporting (73 cities, mainly in developing countries), and data collected by Peking University (83 cities in China). The CDP data being self-reported by cities, we applied quality control procedures, documented the type of emissions and reporting method used, and made a correction to separate CO emissions from those of other greenhouse gases. Further, a set of ancillary data that have a direct or potentially indirect impact on CO emissions were collected from other datasets (e.g. socio-economic and traffic indices) or calculated (climate indices, urban area expansion), then combined with the emission data. We applied several quality controls and validation comparisons with independent datasets. The dataset presented here is not intended to be comprehensive or a representative sample of cities in general, as the choice of cities is based on self-reporting not a designed sampling procedure. 2 2 2

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Planning and Monitoring of Building Energy Demands under Uncertainties by Using IoT Data

Chang S, Castro-Lacouture D, Matsui K, Yamagata Y

Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019 (Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019)     211 - 218 2019

Joint Work,  ISSN  9780784482445

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Building energy models have under predicted actual electricity consumption by about 30%. These models are typically based on physical attributes of an actual building and simulate its operation at static indoor conditions. The attributes of building designs and systems may not represent accurate properties of the building because the data becomes available only as architectural and engineering design progresses. The lack of building data details creates uncertainties in the model. Internet of things (IoT) data enable us to obtain reliable building operational data. This research addresses a major challenge for using IoT data during a building energy prediction and operation. IoT data currently pose two major challenges: 1) IoT data has been generated in existing buildings, but it is often unused, and 2) uncertainties in building energy predictions have resulted in unreliability of the simulation results. The research objective is to present a methodology of IoT-initiated building energy modeling and monitoring to increase the reliability of energy predictions and energy management. The uncertainty-integrated energy modeling enables for reliable energy planning prior to building construction, and for resilient monitoring during post construction and facility operation.

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Real-time sensing in residential area using IoT technology for finding usage patterns to suggest action plan to conserve energy

Matsui K., Yamagata Y., Kawakubo S.

Energy Procedia (Energy Procedia)  158   6438 - 6445 2019

ISSN  18766102

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To conserve energy in a residential sector, showing action plans how to conserve energy is important. However, we need to consider both energy efficiency and indoor comfort. The usage patterns in the residential sector change according to their life style and some people would try to maintain the indoor comfort at high level even paying high energy cost. It is necessary to understand home energy usage patterns in terms of the relationships between indoor comfort and electricity consumption in order to provide appropriate energy saving action plans to the residential sector. For this purpose, in this study we have collected real time data of electricity consumption and indoor temperature using IoT devices and sensors installed to 13 households for about one month in Summer at Sumida ward in Tokyo, Japan. Then, we have analyzed the data using three types of method, which are a clustering algorism to delineate the electricity usage pattern which characterize the household life style, conducted correlation analysis to look at the relationship between electricity consumption, and the indoor temperature for households living in condominium apartments and detached houses with different building structure and ages.

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Urban systems design: A conceptual framework for planning smart communities

Michael B. Tobey, Robert B. Binder, Soowon Chang, Takahiro Yoshida, Yoshiki Yamagata, Perry P. J. Yang

Smart Cities 2 ( 4 ) 522 - 537 2019

Research paper (scientific journal), Joint Work, Accepted

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Urban systems design conceptual framework: Modeling, design, and emergent iterative smart communities

Michael Tobey, Robert Binder, Soowon Chang, Takahiro Yoshida, Yoshiki Yamagata, Perry Yang

Proceedings of the 16th International Conference on Computers in Urban Planning and Urban Management 798833 2019

Research paper (international conference proceedings), Joint Work, Accepted

Urban systems design case study: Tokyo's Sumida ward

Michael B. Tobey, Robert B. Binder, Takahiro Yoshida, Yoshiki Yamagata

Smart Cities 2 ( 4 ) 453 - 470 2019

Research paper (scientific journal), Joint Work, Accepted

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Urban systems design applicability case study: Applying urban systems design framework to North Sumida Ward Tokyo

Michael Tobey, Robert Binder, Takahiro Yoshida, Yoshiki Yamagata

Proceedings of the 16th International Conference on Computers in Urban Planning and Urban Management 798881 2019

Research paper (international conference proceedings), Joint Work, Accepted

Estimating quasi-real-time building energy demand using occupancy information: A case study in Sumida, Tokyo

Takahiro Yoshida, Yoshiki Yamagata, Anna Ebata, Daisuke Murakami, Kanae Matsui

Proceedings of the CIB World Building Congress 2019    130 - 136 2019

Research paper (international conference proceedings), Joint Work, Accepted

Trandformative model of urban buildings optimizing energy demands, solar harvesting potential, and indoor thermal comfort

Soowon Chang, Takahiro Yoshida, Michael Tobey, Yoshiki Yamagata, Perry Yang

Proceedings of the 11th International Conference on Applied Energy 0355 2019

Research paper (international conference proceedings), Joint Work, Accepted

The relationships between energy consumption and surface temperature: A combining multiple-scale observations approach

Takahiro Yoshida, Soowon Chang, Daisuke Murakami, Yoshiki Yamagata

Proceedings of the 11th International Conference on Applied Energy 0940 2019

Research paper (international conference proceedings), Joint Work, Accepted

Spatially detail urban carbon mapping: Integration of top-down and bottom-up approaches

Takahiro Yoshida, Yoshiki Yamagata, Daisuke Murakami

Proceedings of the 15th International Conference on Geocomputation 7.3 2019

Research paper (international conference proceedings), Joint Work, Accepted

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Modeling uncertainty in electricity resilient community clustering: a spatial BigData approach

Yoshiki Yamagata, Takahiro Yoshida, Daisuke Murakami

Proceedings of the CIB World Building Congress 2019    123 - 129 2019

Research paper (international conference proceedings), Joint Work, Accepted

Measuring resiliencce, economy, sustainability, and human well-being in multiple scales for urban diagnostics

Michael Tobey, Soowon Chang, Takahiro Yoshida, Robert Binder, Yoshiki Yamagata

Proceedings of the 11th International Conference on Applied Energy 0904 2019

Research paper (international conference proceedings), Joint Work, Accepted

Individual level heat risk evaluation using GPS towards smart navigation system

Takahiro Yoshida, Yoshiki Yamagata, Daisuke Murakami

Proceedings of the International Cartographic Association 2   152 2019

Research paper (international conference proceedings), Joint Work, Accepted

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Experiential modelling of urban street: a combining approach with neural image assessment and street experiment

Yoshiki Yamagata, Takahiro Yoshida, Haruna Matsui, Perry Yang, Chen Helen

Proceedings of the 15th International Conference on Geocomputation 8.6 2019

Research paper (international conference proceedings), Joint Work, Accepted

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Cost-optimal pathways to decarbonize urban energy systems with PV, batteries, and electric vehicles: A case study for Kyoto, Japan

Takuro Kobashi, Takahiro Yoshida, Katsuhiko Naito, Stefan Pfenninger, Yoshiki Yamagata

Proceedings of the 11th International Conference on Applied Energy 0107 2019

Research paper (international conference proceedings), Joint Work, Accepted

Carbon emission intensities of each building typology: Towards a standardized framework

Takahiro Yoshida, Michael Tobey, Soowon Chang, Yoshiki Yamagata

Proceedings of the 16th International Conference on Computers in Urban Planning and Urban Management 799185 2019

Research paper (international conference proceedings), Joint Work, Accepted

A sustainability provision system of energy demands and indoor thermal comfort by integrating building energy models with IoT: Focusing on residential building in Kyojima, Tokyo

Soowon Chang, Takahiro Yoshida, Kanae Matsui, Daniel Castro-Lacouture, Yoshiki Yamagata

Proceedings of the CIB World Building Congress 2019    137 - 146 2019

Research paper (international conference proceedings), Joint Work, Accepted

Sensitivity of the subspace method for land cover classification

Bagan H., Li H., Yang Y., Takeuchi W., Yamagata Y.

Egyptian Journal of Remote Sensing and Space Science (Egyptian Journal of Remote Sensing and Space Science)  21 ( 3 ) 383 - 389 2018.12

ISSN  11109823

　View Summary

The quality of a supervised classification map depends on the quality of the ground reference data and the classification method used. However, training samples for agriculture landscapes are often mixed with noise. Therefore, the classification of agriculture regions using remotely sensed data requires the use of classification methods with good generalization capabilities. In this study, the performance of the subspace method in land cover classification of a complex cropping mix area is explored. Landsat-5 thematic mapper (TM) data were used to classify 12 different land cover classes in the study area, located between Tianjin and Tangshan cities in northern China. We compared the classification maps obtained using the subspace method with those obtained using the self-organizing map neural network (SOM) and maximum likelihood classification (MLC) methods. The results of this comparative study confirm that the subspace method performed better than both the SOM and MLC methods. Furthermore, a comparison of the sensitivity of these methods to the reduction in the training sample size shows that the subspace method has a lower sensitivity to variations in the number of training pixels used than the other two methods. Our results demonstrate the ability of the subspace method to distinguish between different crop types over a large area. Moreover, the subspace method is less sensitive to small training sample sizes than the other two methods.

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Seasonal urban carbon emission estimation using spatial micro Big Data

Yamagata Y., Yoshida T., Murakami D., Matsui T., Akiyama Y.

Sustainability (Switzerland) (Sustainability (Switzerland))  10 ( 12 )  2018.11

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The objective of this study is to map direct and indirect seasonal urban carbon emissions using spatial micro Big Data, regarding building and transportation energy-use activities in Sumida, Tokyo. Building emissions were estimated by considering the number of stories, composition of use (e.g., residence and retail), and other factors associated with individual buildings. Transportation emissions were estimated through dynamic transportation behaviour modelling, which was obtained using person-trip surveys. Spatial seasonal emissions were evaluated and visualized using three-dimensional (3D) mapping. The results suggest the usefulness of spatial micro Big Data for seasonal urban carbon emission mapping; a process which combines both the building and transportation sectors for the first time with 3D mapping, to detect emission hot spots and to support community-level carbon management in the future.

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Analysis of spatiotemporal land cover changes in Inner Mongolia using self-organizing map neural network and grid cells method

Li Z., Bagan H., Yamagata Y.

Science of the Total Environment (Science of the Total Environment)  636   1180 - 1191 2018.09

ISSN  00489697

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Land use has changed dramatically in the Inner Mongolia Autonomous Region because of rapid economic growth and human disturbances. However, little information is available about the medium- and long-term land use changes in this region. The effects of ecological recovery policies have also been evaluated rarely. In this study, we employed the self-organizing map neural network method to identify the land cover changes in Inner Mongolia between 2000 and 2014. MOD13Q1, Landsat, and DMSP/OLS night-time light data were used as the data resources. The dynamic change map was characterized using the grid cell method. The results showed that urban area of Inner Mongolia increased by more than five times during the 15-year study period, while the mining area also increased. In addition, 35.3% of the farmland was changed into grassland, which may have been caused by the “Grain to Green” policy. The most significant environmental issue in Inner Mongolia is the loss of wetland. >40% of the wetland was converted into other land use types between 2000 and 2014. Grassland increased by 6.05%, but areas of open water and woodland remained about the same. In terms of the geographical distribution, cropland increased in the eastern and middle parts of the region. The transformation from wetland to grassland mainly occurred in the north. Grassland degradation occurred in the west. Thus, environmental policy has resulted in some ecological improvements in Inner Mongolia. However, new environmental problems associated with rapid economic development should be addressed in a timely manner.

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Risk implications of long-term global climate goals: Overall conclusions of the ICA-RUS project

Emori S., Takahashi K., Yamagata Y., Kanae S., Mori S., Fujigaki Y.

Sustainability Science (Sustainability Science)  13 ( 2 ) 279 - 289 2018.03

ISSN  18624065

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We have assessed the risks associated with setting 1.5, 2.0, or 2.5 °C temperature goals and ways to manage them in a systematic manner and discussed their implications. The results suggest that, given the uncertainties in climate sensitivity, “net zero emissions of anthropogenic greenhouse gases in the second half of this century” is a more actionable goal for society than the 2 or 1.5 °C temperature goals themselves. If the climate sensitivity is proven to be relatively high and the temperature goals are not met even when the net zero emission goal is achieved, the options left are: (A) accepting/adapting to a warmer world, (B) boosting mitigation, and (C) climate geoengineering, or any combination of these. This decision should be made based on a deeper discussion of risks associated with each option. We also suggest the need to consider a wider range of policies: not only climate policies, but also broader “sustainability policies”, and to envisage more innovative solutions than what integrated assessment models can currently illustrate. Finally, based on a consideration of social aspects of risk decisions, we recommend the establishment of a panel of “intermediate layer” experts, who support decision-making by citizens as well as social and ethical thinking by policy makers.

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Estimating water–food–ecosystem trade-offs for the global negative emission scenario (IPCC-RCP2.6)

Yamagata Y., Hanasaki N., Ito A., Kinoshita T., Murakami D., Zhou Q.

Sustainability Science (Sustainability Science)  13 ( 2 ) 301 - 313 2018.03

ISSN  18624065

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Negative emission technologies such as bioenergy with carbon capture and storage (BECCS) are regarded as an option to achieve the climatic target of the Paris Agreement. However, our understanding of the realistic sustainable feasibility of the global lands for BECCS remains uncertain. In this study, we assess the impact of BECCS deployment scenarios on the land systems including land use, water resources, and ecosystem services. Specifically, we assess three land-use scenarios to achieve the total amount of 3.3 GtC year (annual negative emission level required for IPCC-RCP 2.6) emission reduction by growing bioenergy crops which requires huge use of global agricultural and forest lands and water. Our study shows that (1) vast conversion of food cropland into rainfed bio-crop cultivation yields a considerable loss of food production that may not be tolerable considering the population increase in the future. (2) When irrigation is applied to bio-crop production, the bioenergy crop productivity is enhanced. This suppresses the necessary area for bio-crop production to half, and saves the land for agricultural productions. However, water consumption is doubled and this may exacerbate global water stress. (3) If conversion of forest land for bioenergy crop cultivation is allowed without protecting the natural forests, large areas of tropical forest could be used for bioenergy crop production. Forest biomass and soil carbon stocks are reduced, implying degradation of the climate regulation and other ecosystem services. These results suggest that without a careful consideration of the land use for bioenergy crop production, a large-scale implementation of BECCS could negatively impact food, water and ecosystem services that are supporting fundamental human sustainability. −1

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Performance-based model for vertical urbanism

Yang P.P.J, Wu Y, Peng Z, Li L, Tobey M, Yamagata Y

Vertical Urbanism: Designing Compact Cities in China (Vertical Urbanism: Designing Compact Cities in China)     149 - 169 2018.01

Joint Work,  ISSN  9781138208995

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This chapter investigates a model to integrate performance measure and urban design in the context of a high-density urban environment. The objective of this research is to discuss how performance-based modeling can be used for addressing problems of energy self-sufficiency and thermal comfort in a vertical and complex urban environment, in which increasing density may cause climate and ecological consequences. An urban neighborhood in Misono of Tokyo’s metropolitan region is studied to test the relationship between vertical urban form and energy performance. Benchmarking the performance behind urban form and neighborhood typologies leads to criteria of high performance and low carbon emission. The chapter discusses the policy implications of performance-based urban design and development in the context of the Misono Smart City Project, a site for Tokyo’s 2020 Olympics, and proposes a transformative approach to generate better performance for an energy resilient and sustainable urban future.

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Global negative emission land use scenarios and their ecological implications

Yamagata Y

Encyclopedia of Ecology (Encyclopedia of Ecology)     96 - 107 2018.01

Single Work,  ISSN  9780444641304

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Earth’s atmospheric CO level has increased beyond 400 ppm and still continuing to rise. In fact, this is the highest level in the last 2 million years. It appears we are heading towards an overshoot of CO concentration before stabilizing green house gases (GHGs) to keep global warming below dangerous level. In Paris on December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) agreed to strengthen the global response to the threat of climate change by keeping a global temperature rise this century well below 2° celsius above preindustrial levels and to pursue efforts to limit the temperature increase even further to 1.5° celsius. Can this level of CO stabilization still be achieved? One core strategies in the mitigation mix are negative emissions technologies (NETs) which are also explicitly described as important options in many IPCC (AR5) CO emission scenarios. Among others, BioEnergy with Carbon Capture and Storage (BECCS) are shown their potential for CO removable from the atmosphere. BECCS as the NETs are most widely selected by integrated assessment models (IAMs) to meet the requirements of temperature limits of 2° and below. It is based on assumed carbon-neutral bioenergy combined with capture of CO produced by combustion and its subsequent storage in geological or ocean repositories. BECCS is a net transfer of CO from the atmosphere into geological layers. However, its credibility as a climate change mitigation option and their impacts to global and regional ecosystems are still unknown. To explore the ecosystem impacts of the large-scale deployment of negative emission land use scenarios, we review some papers that are analyzing global impacts of the land use scenarios on various factors of ecosystem services to look at the sustainability limits to their global large scale deployments. Ecological services implications of the NETs especially land demanding BECCS land use scenarios need to be addressed before implementing such projects not only for achieving global low carbon target but also achieving more comprehensive ecological sustainabilities to meet the sustainable development goals (SDGs). 2 2 2 2 2 2 2

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Urban carbon mapping: Towards a standardized framework

Sharifi A., Wu Y., Khamchiangta D., Yoshida T., Yamagata Y.

Energy Procedia (Energy Procedia)  152   799 - 808 2018

ISSN  18766102

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Cities are responsible for a large share of global energy consumption and CO2 emissions. Significant reduction of urban energy consumption and CO2 emissions is essential for meeting the ambitious climate stabilization targets. This hinges on having adequate understanding of the patterns and trends of emissions. It is essential to create datasets of cities emissions and utilize mapping techniques to inform planners and decision makers about the dynamics of urban carbon emissions. Due to the openness of cities and issues related to availability and accessibility of urban energy consumption data, this is a challenging task. It is critical to develop consistent methods for mapping emissions. Such methods and frameworks should enable cities to map their emissions with minimum data requirements. They should also be applicable to different cities across the world. As a preliminary effort, this study introduces a framework for synthesizing building and transport energy consumption data with the Local Climate Zones (LCZs) classification system. Drawing on preliminary results from applying the framework to Bangkok, Shanghai, and Tokyo, we explain how this approach can provide opportunities for standardizing urban carbon accounting. The paper concludes with suggestions for improving granularity and accuracy of emissions accounting. The concept of Local Energy Zones (LEZs) is introduced and is suggested to be used as a potentially suitable concept for analysing CO2 emissions dynamics of cities.

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Spatially Explicit Land-Use Modelling for Assessing Climate-Resilient Sustainable Urban Forms

Yamagata Y., Murakami D.

Lecture Notes in Energy (Lecture Notes in Energy)  65   213 - 228 2018

ISSN  9783319757971

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Climate resiliency is a key topic for cities across the world especially after the Paris Agreement. By combing socio-economic situations, carbon emission reduction, disaster risk management, and other factors determine sustainability of cities, we need to understand trade-offs among these factors. In other words, wise urban systems design are required in cities in the world. Especially in the developed countries like Japan which are expected to experience unprecedented pollution decrease, we need to achieve “wise shrink” of cities that are desirable from multiple viewpoints. With such a background, we introduce our spatially-explicit urban land-use model (SULM) as a tool to analyze the trade-offs among climate resilient sustainability. The SULM is applied to an analysis in the Tokyo metropolitan area to analyze the implications of Business-As-usual (BAU), Compact city, and Wise shrink land use scenarios. SULM could be a useful tool for assessing urban resiliency against climate extreme events for eco-urbanism oriented land forms.

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Mapping building carbon emissions within local climate zones in Shanghai

Wu Y., Sharifi A., Yang P., Borjigin H., Murakami D., Yamagata Y.

Energy Procedia (Energy Procedia)  152   815 - 822 2018

ISSN  18766102

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The carbon emission pattern of the built environment is closely associated with its morphological and functional structures. Based on the online volunteered geographic information and some publicly available official data sources, this study intends to provide a standardized framework for estimating the indirect building carbon emissions within the boundaries of various types of Local Climate Zones (LCZs), to better forecast the LCZ carbon emission patterns and assist district wide energy management. The whole research is devised into four sequential sections: First, the statistics of energy use intensity of different building uses (including residential and non-residential buildings) are retrieved from official data sources using a down-scaled approach; then a random forest machine learning method is applied to automatically identify building uses based on the training samples; next, a GIS method is developed to delineate the LCZs in Shanghai utilizing calculated urban form and land cover parameters; finally, the building carbon emission values are linked to the LCZs to determine the emission coefficient of different LCZ categories in Shanghai.

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Resilience-Oriented Urban Planning

Sharifi A., Yamagata Y.

Lecture Notes in Energy (Lecture Notes in Energy)  65   3 - 27 2018

ISSN  9783319757971

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The concept of resilience is increasingly used in scientific and political discourses on sustainable urban development and urban disaster risk reduction. It has its roots in disciplines such as physics, psychology and ecology and is a relatively new concept in the field of urban planning. This chapter aims to explore the implications of integrating resilience thinking into urban planning. It introduces the concept of resilience-oriented urban planning and discusses how it is distinct from conventional urban planning. Extending the theory of adaptive cycle, it is argued that urban planning should not be considered as a static process. Urban systems are dynamic entities characterized by non-equilibrium dynamics and constantly go through the four phases of ‘exploitation’, ‘conservation’, ‘release’, and ‘reorganization’. Resilience-oriented planning is needed to address dynamics and complexities of urban systems. This chapter provides discussions on paradigm shifts that are needed to integrate resilience thinking into urban planning. These paradigm shifts are discussed in the context of different planning themes, namely, strategy making and visioning, public participation, equity and empowerment, learning from traditional local knowledge, institutional reforms, social networks, sectoral and spatio-temporal dynamics, land use planning, and urban infrastructure. The chapter concludes with some discussions on how these paradigm shifts contribute to integrating principles that underpin the concept of resilience into urban planning and design.

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Resilient Urban Form: A Conceptual Framework

Sharifi A., Yamagata Y.

Lecture Notes in Energy (Lecture Notes in Energy)  65   167 - 179 2018

ISSN  9783319757971

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Resilience is widely recognized as a pre-requisite for achieving sustainability. Despite the wealth of research on urban resilience, no comprehensive work has been published on the association between urban form and resilience. Form of cities can affect their capacity to survive and thrive in the face of adverse events. Better understanding of the concept of ‘resilient urban form’ and ‘resilient urban form typologies’ is, therefore, essential for achieving more advances in urban resilience. It is essential to elucidate the meaning of ‘resilient urban form’ and explain what issues should be considered to achieve resilient urban morphologies. This chapter elaborates on the concept of ‘resilient urban form’ and introduces a conceptual framework that can be used for its assessment. The conceptual framework emphasizes paying attention to the following issues: ‘resilience of what?’, ‘resilience at what geographic and temporal scale?’, ‘resilience to what’, and ‘resilience for what?’. To answer the first question, various underlying components of urban form should be identified. The issue of ‘resilience at what geographic scale?’ implies that dynamics and interactions across various geographic scales need to be considered. Certain urban form components may be relevant to multiple scales and have different and even opposing affects across different scales. The question of ‘resilience at what temporal scale?’ indicates that, for example, certain urban forms may be desirable when the growth speed of the city is high, but detrimental after it reaches its growth limit. The question of ‘resilience to what?’ is important as certain forms may be favorable in terms of resilience to some hazards but undesirable with respect to others. Finally, elaboration on the question ‘resilience for what?’ helps better understand what specific resilience qualities can be improved through promoting favorable urban forms. The conceptual framework can be utilized to further elucidate the nature of relationships between different components of urban form and resilience of cities. It can also be used to assess resilience of different urban forms across different geographical and temporal scales.

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Dynamic carbon mapping with micro-urban simulations towards urban system design of near zero

Takahiro Yoshida, Yoshiki Yamagata, Daisuke Murakami

Proceedings of the Council of Engineering Systems Universities 2018 Global Conference    SU2-1 2018

Research paper (international conference proceedings), Joint Work, Accepted

Resilience-Oriented Urban Planning Theoretical and Empirical Insights Preface

Yamagata Yoshiki, Sharifi Ayyoob

RESILIENCE-ORIENTED URBAN PLANNING: THEORETICAL AND EMPIRICAL INSIGHTS 65   V - VI 2018

Joint Work,  ISSN  978-3-319-75797-1